Write manifests for the eight intro statics, and check them against upstream

AGENTS.md

@@ -43,6 +43,8 @@ Both are cheap to follow and expensive to discover. `PLAN.md` carries the reason
 - **Never delete a file a sibling repo reads.** `lecture-wasm` fetches `lecture-python-intro`'s *committed blobs* by URL, so deleting intro's copy in a repoint PR 404s the wasm build immediately. "Delete the lecture repo's own copy in the same repoint PR" applies only where no sibling reads it; where one does, the sibling's repoint lands first or in the same set.
 - **Repoint every consumer of a dataset together.** The strict audit has no green state for a partially-repointed dataset — `pending`/`landed` fails once any consumer reads data-lectures, and `repointed`/`final` fails while any consumer still does not. Land the lecture repoints first, then flip `migration.yml`; that flip is the push that re-runs the audit, so reality and the tracker agree by the time it runs.
 
+- **A migration moves bytes; it does not update them.** Land the copy the lectures already consume, validated byte-identical — that is what makes a repoint provably unable to change a figure. If the committed file differs from what upstream publishes today, migrate it unchanged anyway, record the delta in `integrity.upstream` **and** in the register at [#39](https://github.com/QuantEcon/data-lectures/issues/39), and leave the decision for after the migration. Adopting a newer vintage changes lecture output and is an author's call, not an infrastructure one — and per "Corrections vs vintages" below it gets a **new filename**, never a silent replacement.
+
 Cross-repo repoints are worked from [`QuantEcon/workspace-lectures`](https://github.com/QuantEcon/workspace-lectures) — same branch name in each repo, one PR per repo, no aggregate PR.
 
 ### Corrections vs vintages

CATALOG.md

@@ -4,23 +4,31 @@
 
 # Dataset catalog — `QuantEcon/data-lectures`
 
-The migrated-dataset registry, **auto-generated** from the sidecar manifests (`lectures/*.yml`). Do not edit by hand — run `python scripts/build_catalog.py`. A dataset appears here once it has a manifest; files not yet migrated are tracked in [PLAN.md](PLAN.md) Phase 9.
+The dataset registry, **auto-generated** from the sidecar manifests (`lectures/*.yml`). Do not edit by hand — run `python scripts/build_catalog.py`. A dataset appears here once it has a manifest, which may be before its consuming lectures are repointed — an empty **Used by** column means the file is here and documented but no lecture reads it from this repo yet. Files still to migrate are tracked in [PLAN.md](PLAN.md).
 
-**10 datasets migrated** · 2.4 MB total · 9 permitted / 1 restricted redistribution
+**18 datasets** · 10 read by lectures today, 8 awaiting repoint · 5.3 MB total · 17 permitted / 1 restricted redistribution
 
 | Dataset | Class | Source | Licence | Redist. | Integrity | Builder | Size | Used by |
 | --- | --- | --- | --- | --- | --- | --- | --- | --- |
 | [**ames_house_prices.csv**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/ames_house_prices.csv)<br><sub>Ames, Iowa — residential house sales, 2006-2010</sub> | constructed | [Ames Housing data (De Cock 2011), Journal of Statistics Education](http://jse.amstat.org/v19n3/decock.pdf) |  | ✅ permitted | ✅ verified | ✅ committed | 75.2 KB | [lecture-python-intro · observed_distributions.md](https://github.com/QuantEcon/lecture-python-intro/blob/main/lectures/observed_distributions.md)<br>[lecture-python-intro · fitting_distributions.md](https://github.com/QuantEcon/lecture-python-intro/blob/main/lectures/fitting_distributions.md) |
+| [**assignat.xlsx**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/assignat.xlsx)<br><sub>French Revolution — assignat issues, budgets and seigniorage (Sargent-Velde)</sub> | verbatim | [Sargent and Velde, "Macroeconomic Features of the French Revolution" — supporting spreadsheets](https://www.journals.uchicago.edu/doi/10.1086/261992) |  | ✅ permitted | ⚠️ unverifiable | n/a (verbatim) | 204.6 KB | — |
+| [**caron.npy**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/caron.npy)<br><sub>French Revolution — monthly specie value of the assignat, 1791-1796</sub> | constructed | unrecorded |  | ✅ permitted | ⚠️ unverifiable | ⚠️ unrecovered | 1.1 KB | — |
+| [**chapter_3.xlsx**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/chapter_3.xlsx)<br><sub>The Ends of Four Big Inflations — appendix tables, transcribed</sub> | constructed | [Sargent, "Rational Expectations and Inflation", chapter 3 appendix tables](https://press.princeton.edu/books/paperback/9780691158709/rational-expectations-and-inflation) |  | ✅ permitted | ⚠️ unverifiable | ⚠️ unrecovered | 71.6 KB | — |
 | [**countries.csv**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/countries.csv)<br><sub>WorldData.info country reference table</sub> | verbatim | [WorldData.info — country data downloads](https://www.worlddata.info/downloads/) | Proprietary — © WorldData.info, all rights reserved | ⚠️ restricted | ⚠️ unverifiable | n/a (verbatim) | 48.4 KB | [lecture-python-programming · pandas_panel.md](https://github.com/QuantEcon/lecture-python-programming/blob/main/lectures/pandas_panel.md)<br>[lecture-python.myst · pandas_panel.md](https://github.com/QuantEcon/lecture-python.myst/blob/main/lectures/pandas_panel.md) |
+| [**dette.xlsx**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/dette.xlsx)<br><sub>French Revolution — public debt, military spending and revenues (Sargent-Velde)</sub> | verbatim | [Sargent and Velde, "Macroeconomic Features of the French Revolution" — supporting spreadsheets](https://www.journals.uchicago.edu/doi/10.1086/261992) |  | ✅ permitted | ⚠️ unverifiable | n/a (verbatim) | 617.2 KB | — |
 | [**employ.csv**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/employ.csv)<br><sub>Eurostat employment in Europe — by age and sex, 2007–2016</sub> | constructed | [Eurostat — Employment database](https://ec.europa.eu/eurostat/data/database) | Eurostat reuse (Commission Decision 2011/833/EU) | ✅ permitted | ⚠️ unverifiable | ⚠️ unrecovered | 1.6 MB | [lecture-python-programming · pandas_panel.md](https://github.com/QuantEcon/lecture-python-programming/blob/main/lectures/pandas_panel.md)<br>[lecture-python.myst · pandas_panel.md](https://github.com/QuantEcon/lecture-python.myst/blob/main/lectures/pandas_panel.md) |
 | [**epl_match_goals.csv**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/epl_match_goals.csv)<br><sub>English Premier League — full-time scores, 2015-16 to 2024-25</sub> | constructed | [openfootball / football.json](https://github.com/openfootball/football.json) | Public domain | ✅ permitted | ✅ verified | ✅ committed | 203.2 KB | [lecture-python-intro · fitting_distributions.md](https://github.com/QuantEcon/lecture-python-intro/blob/main/lectures/fitting_distributions.md) |
+| [**fig_3.xlsx**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/fig_3.xlsx)<br><sub>French Revolution — figure 3 series (Sargent-Velde)</sub> | verbatim | [Sargent and Velde, "Macroeconomic Features of the French Revolution" — supporting spreadsheets](https://www.journals.uchicago.edu/doi/10.1086/261992) |  | ✅ permitted | ⚠️ unverifiable | n/a (verbatim) | 9.2 KB | — |
 | [**japan_deaths_by_age.csv**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/japan_deaths_by_age.csv)<br><sub>Japan — deaths by single year of age, 2023</sub> | constructed | [United Nations, Department of Economic and Social Affairs, Population Division — World Population Prospects 2024](https://population.un.org/wpp/downloads) | CC BY 3.0 IGO | ✅ permitted | ✅ verified | ✅ committed | 1.7 KB | [lecture-python-intro · observed_distributions.md](https://github.com/QuantEcon/lecture-python-intro/blob/main/lectures/observed_distributions.md)<br>[lecture-python-intro · fitting_distributions.md](https://github.com/QuantEcon/lecture-python-intro/blob/main/lectures/fitting_distributions.md) |
 | [**japan_earthquakes.csv**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/japan_earthquakes.csv)<br><sub>Japan region — earthquakes of magnitude 5 and above, 2000-2024</sub> | constructed | [Advanced National Seismic System (ANSS) Comprehensive Earthquake Catalog (ComCat), US Geological Survey](https://earthquake.usgs.gov/earthquakes/search/) | US Government work — public domain | ✅ permitted | ✅ verified | ✅ committed | 172.8 KB | [lecture-python-intro · fitting_distributions.md](https://github.com/QuantEcon/lecture-python-intro/blob/main/lectures/fitting_distributions.md) |
 | [**japan_population_by_age.csv**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/japan_population_by_age.csv)<br><sub>Japan — population by single year of age, 2024</sub> | constructed | [Population Estimates, Statistics Bureau of Japan, Ministry of Internal Affairs and Communications](https://www.stat.go.jp/english/data/jinsui/index.html) | Japan Statistics Bureau terms of use | ✅ permitted | ✅ verified | ✅ committed | 1.3 KB | [lecture-python-intro · prob_dist.md](https://github.com/QuantEcon/lecture-python-intro/blob/main/lectures/prob_dist.md) |
 | [**lingcod_msy_recovery.csv**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/lingcod_msy_recovery.csv)<br><sub>Pacific Coast lingcod — biomass and fishing pressure relative to MSY</sub> | constructed | [RAM Legacy Stock Assessment Database](https://www.ramlegacy.org/) | CC BY 4.0 | ✅ permitted | ⚠️ unverifiable | ⚠️ unrecovered | 2.3 KB | [lecture-python-intro · msy_fishery.md](https://github.com/QuantEcon/lecture-python-intro/blob/main/lectures/msy_fishery.md) |
+| [**longprices.xls**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/longprices.xls)<br><sub>Price levels in four hard-currency countries, 1600-2000</sub> | verbatim | [Sargent and Velde, "The Big Problem of Small Change" — supporting data](https://press.princeton.edu/books/hardcover/9780691116358/the-big-problem-of-small-change) |  | ✅ permitted | ⚠️ unverifiable | n/a (verbatim) | 379.5 KB | — |
+| [**mpd2020.xlsx**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/mpd2020.xlsx)<br><sub>Maddison Project Database 2020 — GDP per capita and population, 1 CE to 2018</sub> | constructed | [Maddison Project Database, version 2020](https://www.rug.nl/ggdc/historicaldevelopment/maddison/releases/maddison-project-database-2020) | CC BY 4.0 | ✅ permitted | ⇄ diverged | ⚠️ unrecovered | 1.7 MB | — |
+| [**nom_balances.npy**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/nom_balances.npy)<br><sub>French Revolution — monthly nominal assignat balances, 1789-1796</sub> | constructed | unrecorded |  | ✅ permitted | ⚠️ unverifiable | ⚠️ unrecovered | 1.4 KB | — |
 | [**realwage.csv**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/realwage.csv)<br><sub>OECD real minimum wages — 32 countries, 2006–2016</sub> | constructed | [OECD — Real minimum wages (RMW)](https://stats.oecd.org/Index.aspx?DataSetCode=RMW) | CC BY 4.0 | ✅ permitted | ⚠️ unverifiable | ⚠️ unrecovered | 118.7 KB | [lecture-python-programming · pandas_panel.md](https://github.com/QuantEcon/lecture-python-programming/blob/main/lectures/pandas_panel.md)<br>[lecture-python.myst · pandas_panel.md](https://github.com/QuantEcon/lecture-python.myst/blob/main/lectures/pandas_panel.md) |
 | [**us_adult_heights.csv**](https://github.com/QuantEcon/data-lectures/raw/main/lectures/us_adult_heights.csv)<br><sub>United States — adult standing height by sex, NHANES 2015-2018</sub> | constructed | [National Health and Nutrition Examination Survey (NHANES), US Centers for Disease Control and Prevention, National Center for Health Statistics](https://www.cdc.gov/nchs/nhanes/index.htm) | US Government work — public domain | ✅ permitted | ✅ verified | ✅ committed | 123.1 KB | [lecture-python-intro · prob_dist.md](https://github.com/QuantEcon/lecture-python-intro/blob/main/lectures/prob_dist.md)<br>[lecture-python-intro · observed_distributions.md](https://github.com/QuantEcon/lecture-python-intro/blob/main/lectures/observed_distributions.md)<br>[lecture-python-intro · fitting_distributions.md](https://github.com/QuantEcon/lecture-python-intro/blob/main/lectures/fitting_distributions.md) |
 
 ---
 
-**Legend** — *Integrity* is the `integrity.upstream.status` (is this what the source says?): ✅ verified · ◑ spot-checked · ⚠️ unverifiable · … unverified · ❌ failing. *Redist.* ⚠️ restricted files are cached as inherited exposures and tracked for licence review ([workspace-lectures#20](https://github.com/QuantEcon/workspace-lectures/issues/20)). *Builder* ⚠️ unrecovered marks a constructed dataset whose builder was never committed (PLAN Phase 9).
+**Legend** — *Integrity* is the `integrity.upstream.status` (is this what the source says?): ✅ verified · ◑ spot-checked · ⇄ diverged (checked, differs, delta known and tracked) · ⚠️ unverifiable · … unverified · ❌ failing. *Redist.* ⚠️ restricted files are cached as inherited exposures and tracked for licence review ([workspace-lectures#20](https://github.com/QuantEcon/workspace-lectures/issues/20)). *Builder* ⚠️ unrecovered marks a constructed dataset whose builder was never committed (PLAN Phase 9).

PLAN.md

@@ -42,7 +42,7 @@ This repository is being shaped into the **single canonical repository for data
 
 ## Repoint rules
 
-Two rules learned the hard way. Both are about *ordering*, both are cheap to follow and expensive to discover, and neither is enforced by CI — the strict audit catches the second only after the fact.
+Three rules learned the hard way. The first two are about *ordering*, both cheap to follow and expensive to discover, and neither is enforced by CI — the strict audit catches the second only after the fact. The third is about *scope*.
 
 ### 1. Repoint a sibling reader before deleting the file it reads
 
@@ -60,6 +60,22 @@ The strict audit has **no green state for a partially-repointed dataset**. `scri
 
 Practically: one branch name across data-lectures + every consuming repo, PRs opened together, lecture repoints merged first, then the `migration.yml` flip to `repointed` — that last push is what re-runs the audit, and by then reality and the tracker agree.
 
+### 3. A migration moves bytes; it does not update them
+
+The copy that lands here is the copy the lectures **already consume**, validated byte-identical in the repoint PR. That is what makes a repoint safe to merge: it provably cannot change a single figure.
+
+Adopting a newer upstream vintage is a *different change* with a different risk profile — it does change lecture output, it needs figures re-reviewed, and it is an author-facing decision rather than an infrastructure one. Conflating the two turns every repoint into a content review and stalls the programme.
+
+So when a migration finds that the committed file differs from what upstream publishes today:
+
+1. **Migrate what the lectures use**, unchanged, with the byte-compare gate as normal.
+2. **Record the delta** in the dataset's manifest (`integrity.upstream`) *and* in the register at [#39](https://github.com/QuantEcon/data-lectures/issues/39) — the manifest makes it visible in the catalog from day one, the register is where it gets reasoned about.
+3. **Review the register once the migration completes**, and decide each case on its merits.
+
+Two deltas look alike and need opposite responses. *Upstream moved* — a newer vintage exists; adopting it means a **new filename**, per "Corrections vs vintages" in `AGENTS.md`, so consumers opt in. *Our copy diverges* — upstream is unchanged but our file was modified; resolving means reconciling the edit. `mpd2020.xlsx` is the first recorded instance of the second kind, and it is instructive: the local edits are load-bearing for the consuming lecture, so the file and the lecture have to move together.
+
+Detecting these automatically rather than by accident is proposed in [#40](https://github.com/QuantEcon/data-lectures/issues/40).
+
 ## Migration tracks
 
 The remaining work decomposes by **consuming series** rather than by hosting pattern, because — apart from the `intro`/`wasm` pairing — each series now owns its own data. This is the execution view; the phases below remain the machinery each track passes through.